The short-term optimal resource allocation approach for electric vehicles and V2G service stations

Abstract

As more electric vehicles (EVs) participate in vehicle-to-grid (V2G) service, the large-scale EV-pile resource allocation problem is becoming a key issue that affects system operation and user participation. EV user preference and decision-making uncertainty can affect V2G scheduling, potentially causing an imbalance between the dispatchable capacities of aggregated EVs and the power required in service stations. To improve the utilization rates of EV batteries and charging/discharging piles, this study proposes a vehicle-pile resource allocation approach based on a two-stage categorical hierarchical scheduling framework to solve the vehicle-pile assignment problem in near real time. It also develops a new hybrid clustering algorithm and a vehicle-pile resource assignment model that considers user preferences and requirements in the upper layer, and operational cost reduction in the lower layer. The effectiveness of the proposed algorithm and model are verified by simulation cases to achieve an 88% actual power matching degree and a 25% cost reduction. Moreover, the credit priority strategy is proposed and designed for the selection of EVs with higher dispatchability to ensure the effective implementation of allocation solutions.